光电技术应用, 2019, 34 (3): 12, 网络出版: 2019-07-25  

基于图像处理的钢板缺陷检测方法

Defect Detection of Steel Plate Based on Image Processing
作者单位
内蒙古科技大学 信息工程学院, 包头 014000
摘要
针对光照不均等对钢板缺陷检测识别率的影响, 提出了一种基于图像处理的钢板缺陷检测方法。在图像增强的基础上进行图像滤波去噪, 保留图像细节特征。根据大津阈值法实现图像分割, 对钢板缺陷图像周长、面积及宽度等几何特征进行有效提取并根据神经网络分类识别。实验表明, 所提出的钢板缺陷检测方法在识别准确率方面有所提高。
Abstract
According to the influence on the low recognition rate of steel plate defect detection for uneven illumination, the algorithm of steel plate defect detection based on image processing is proposed. Based on image enhancement, image filtering and de-noising are performed, and image detailed features are retained. Image segmentation is realized by OSTU algorithm. The geometric features of steel plate defect images such as perimeter, area and width are effectively extracted, classified and recognized based on neural network. Experimental results show that the recognition accuracy of the proposed steel plate defect detection method is improved.

闫俊红, 何家明, 李忠虎. 基于图像处理的钢板缺陷检测方法[J]. 光电技术应用, 2019, 34(3): 12. YAN Jun-hong, HE Jia-ming, LI Zhong-hu. Defect Detection of Steel Plate Based on Image Processing[J]. Electro-Optic Technology Application, 2019, 34(3): 12.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!